Bottom Line:
A multivariate statistical approach demonstrated that in phototrophic organisms, there is a clear influence of the ecological niche on the diversity of Fe uptake systems.Extending the analyses to the metagenome database from the Global Ocean Sampling expedition, we demonstrated that the Fe uptake and homeostasis mechanisms differed significantly across marine niches defined by temperatures and dFe concentrations, and that this difference was linked to the distribution of microbial taxa in these niches.Using the dN/dS ratios (which signify the rate of non-synonymous mutations) of the nucleotide sequences, we identified that genes encoding for TonB, Ferritin, Ferric reductase, IdiA, ZupT, and Fe(2+) transport proteins FeoA and FeoB were evolving at a faster rate (positive selection pressure) while genes encoding ferrisiderophore, heme and Vitamin B12 uptake systems, siderophore biosynthesis, and IsiA and IsiB were under purifying selection pressure (evolving slowly).

ABSTRACTIron (Fe) is an essential micronutrient for many processes in all living cells. Dissolved Fe (dFe) concentrations in the ocean are of the order of a few nM, and Fe is often a factor limiting primary production. Bioavailability of Fe in aquatic environments is believed to be primarily controlled through chelation by Fe-binding ligands. Marine microbes have evolved different mechanisms to cope with the scarcity of bioavailable dFe. Gradients in dFe concentrations and diversity of the Fe-ligand pool from coastal to open ocean waters have presumably imposed selection pressures that should be reflected in the genomes of microbial communities inhabiting the pelagic realm. We applied a hidden Markov model (HMM)-based search for proteins related to cellular iron metabolism, and in particular those involved in Fe uptake mechanisms in 164 microbial genomes belonging to diverse taxa and occupying different aquatic niches. A multivariate statistical approach demonstrated that in phototrophic organisms, there is a clear influence of the ecological niche on the diversity of Fe uptake systems. Extending the analyses to the metagenome database from the Global Ocean Sampling expedition, we demonstrated that the Fe uptake and homeostasis mechanisms differed significantly across marine niches defined by temperatures and dFe concentrations, and that this difference was linked to the distribution of microbial taxa in these niches. Using the dN/dS ratios (which signify the rate of non-synonymous mutations) of the nucleotide sequences, we identified that genes encoding for TonB, Ferritin, Ferric reductase, IdiA, ZupT, and Fe(2+) transport proteins FeoA and FeoB were evolving at a faster rate (positive selection pressure) while genes encoding ferrisiderophore, heme and Vitamin B12 uptake systems, siderophore biosynthesis, and IsiA and IsiB were under purifying selection pressure (evolving slowly).

Mentions:
Figure 4 shows the GOS sample locations overlayed on the annual mean surface bioavailable dFe from the PELAGOS model (Vichi et al., 2007a,b). This model couples the biogeochemical fluxes with global ocean general circulation models. The iron dynamics in PELAGOS include fluxes for uptake of bioavailable Fe by phytoplankton, loss by turnover/cell lysis, and predation. The only external function that forces these fluxes is the monthly deposition of atmospheric Fe and a dissolution fraction of the Fe dust which is set at 1%. We used the surface dFe concentration predictions from the PELAGOS model to characterize the aquatic niches. Since we were using model-derived dFe concentrations in place of actual observations, we compared the dFe concentrations used in this study with those used in Toulza et al. (2012). For the 22 GOS samples where dFe concentration predictions from both of these models were available, an R2 of 0.849 in a linear regression of the dFe values showed a good correlation between the outputs of the two models (Table S2 in Supplementary Material). There was a marked difference in the surface dFe concentration in samples collected from the Atlantic and the Pacific basins. However, apart from the dFe differences in the niches (Open Ocean or Coastal) defined in Toulza et al. (2012), the spatial distribution of the samples across a wide range of latitudes also resulted in a separation along a temperature gradient (Temperate vs. Tropical) (Rusch et al., 2007).

Mentions:
Figure 4 shows the GOS sample locations overlayed on the annual mean surface bioavailable dFe from the PELAGOS model (Vichi et al., 2007a,b). This model couples the biogeochemical fluxes with global ocean general circulation models. The iron dynamics in PELAGOS include fluxes for uptake of bioavailable Fe by phytoplankton, loss by turnover/cell lysis, and predation. The only external function that forces these fluxes is the monthly deposition of atmospheric Fe and a dissolution fraction of the Fe dust which is set at 1%. We used the surface dFe concentration predictions from the PELAGOS model to characterize the aquatic niches. Since we were using model-derived dFe concentrations in place of actual observations, we compared the dFe concentrations used in this study with those used in Toulza et al. (2012). For the 22 GOS samples where dFe concentration predictions from both of these models were available, an R2 of 0.849 in a linear regression of the dFe values showed a good correlation between the outputs of the two models (Table S2 in Supplementary Material). There was a marked difference in the surface dFe concentration in samples collected from the Atlantic and the Pacific basins. However, apart from the dFe differences in the niches (Open Ocean or Coastal) defined in Toulza et al. (2012), the spatial distribution of the samples across a wide range of latitudes also resulted in a separation along a temperature gradient (Temperate vs. Tropical) (Rusch et al., 2007).

Bottom Line:
A multivariate statistical approach demonstrated that in phototrophic organisms, there is a clear influence of the ecological niche on the diversity of Fe uptake systems.Extending the analyses to the metagenome database from the Global Ocean Sampling expedition, we demonstrated that the Fe uptake and homeostasis mechanisms differed significantly across marine niches defined by temperatures and dFe concentrations, and that this difference was linked to the distribution of microbial taxa in these niches.Using the dN/dS ratios (which signify the rate of non-synonymous mutations) of the nucleotide sequences, we identified that genes encoding for TonB, Ferritin, Ferric reductase, IdiA, ZupT, and Fe(2+) transport proteins FeoA and FeoB were evolving at a faster rate (positive selection pressure) while genes encoding ferrisiderophore, heme and Vitamin B12 uptake systems, siderophore biosynthesis, and IsiA and IsiB were under purifying selection pressure (evolving slowly).

ABSTRACTIron (Fe) is an essential micronutrient for many processes in all living cells. Dissolved Fe (dFe) concentrations in the ocean are of the order of a few nM, and Fe is often a factor limiting primary production. Bioavailability of Fe in aquatic environments is believed to be primarily controlled through chelation by Fe-binding ligands. Marine microbes have evolved different mechanisms to cope with the scarcity of bioavailable dFe. Gradients in dFe concentrations and diversity of the Fe-ligand pool from coastal to open ocean waters have presumably imposed selection pressures that should be reflected in the genomes of microbial communities inhabiting the pelagic realm. We applied a hidden Markov model (HMM)-based search for proteins related to cellular iron metabolism, and in particular those involved in Fe uptake mechanisms in 164 microbial genomes belonging to diverse taxa and occupying different aquatic niches. A multivariate statistical approach demonstrated that in phototrophic organisms, there is a clear influence of the ecological niche on the diversity of Fe uptake systems. Extending the analyses to the metagenome database from the Global Ocean Sampling expedition, we demonstrated that the Fe uptake and homeostasis mechanisms differed significantly across marine niches defined by temperatures and dFe concentrations, and that this difference was linked to the distribution of microbial taxa in these niches. Using the dN/dS ratios (which signify the rate of non-synonymous mutations) of the nucleotide sequences, we identified that genes encoding for TonB, Ferritin, Ferric reductase, IdiA, ZupT, and Fe(2+) transport proteins FeoA and FeoB were evolving at a faster rate (positive selection pressure) while genes encoding ferrisiderophore, heme and Vitamin B12 uptake systems, siderophore biosynthesis, and IsiA and IsiB were under purifying selection pressure (evolving slowly).